Collaborative online planning for automated victim search in disaster response
Collaborative online planning for automated victim search in disaster response
Collaboration is essential for effective performance by groups of robots in disaster response settings. Here we are particularly interested in heterogeneous robots that collaborate in complex scenarios with incomplete, dynamically changing information. In detail, we consider an automated victim search setting, where unmanned aerial vehicles (UAVs) with different capabilities work together to scan for mobile phones and find and provide information about possible victims near these phone locations. The state of the art for such collaboration is robot control based on independent planning for robots with different tasks and typically incorporates uncertainty with only a limited scope. In contrast, in this paper, we take into account complex relations between robots with different tasks. As a result, we create a joint, full-horizon plan for the whole robot team by optimising over the uncertainty of future information gain using an online planner with hindsight optimisation. This joint plan is also used for further optimisation of individual UAV paths based on the long-term plans of all robots. We evaluate our planner's performance in a realistic simulation environment based on a real disaster and find that our approach finds victims 25% faster compared to current state-of-the-art approaches.
Hindsight optimisation, Multi-robot teams, Particle filter, Path planning, Search and rescue, Task allocation
251-266
Beck, Zoltán
07dccaf8-4485-43bb-9f9d-1dbbec3461a3
Teacy, W. T.Luke
5f962a10-9ab5-4b19-8016-cc72588bdc6a
Rogers, Alex
60b99721-b556-4805-ab34-deb808a8666c
Jennings, Nicholas R.
ab3d94cc-247c-4545-9d1e-65873d6cdb30
1 February 2018
Beck, Zoltán
07dccaf8-4485-43bb-9f9d-1dbbec3461a3
Teacy, W. T.Luke
5f962a10-9ab5-4b19-8016-cc72588bdc6a
Rogers, Alex
60b99721-b556-4805-ab34-deb808a8666c
Jennings, Nicholas R.
ab3d94cc-247c-4545-9d1e-65873d6cdb30
Beck, Zoltán, Teacy, W. T.Luke, Rogers, Alex and Jennings, Nicholas R.
(2018)
Collaborative online planning for automated victim search in disaster response.
Robotics and Autonomous Systems, 100, .
(doi:10.1016/j.robot.2017.09.014).
Abstract
Collaboration is essential for effective performance by groups of robots in disaster response settings. Here we are particularly interested in heterogeneous robots that collaborate in complex scenarios with incomplete, dynamically changing information. In detail, we consider an automated victim search setting, where unmanned aerial vehicles (UAVs) with different capabilities work together to scan for mobile phones and find and provide information about possible victims near these phone locations. The state of the art for such collaboration is robot control based on independent planning for robots with different tasks and typically incorporates uncertainty with only a limited scope. In contrast, in this paper, we take into account complex relations between robots with different tasks. As a result, we create a joint, full-horizon plan for the whole robot team by optimising over the uncertainty of future information gain using an online planner with hindsight optimisation. This joint plan is also used for further optimisation of individual UAV paths based on the long-term plans of all robots. We evaluate our planner's performance in a realistic simulation environment based on a real disaster and find that our approach finds victims 25% faster compared to current state-of-the-art approaches.
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More information
Accepted/In Press date: 21 September 2017
e-pub ahead of print date: 4 November 2017
Published date: 1 February 2018
Keywords:
Hindsight optimisation, Multi-robot teams, Particle filter, Path planning, Search and rescue, Task allocation
Identifiers
Local EPrints ID: 417775
URI: http://eprints.soton.ac.uk/id/eprint/417775
ISSN: 0921-8890
PURE UUID: 4f0edf4c-cc48-40bc-8bb8-6504ed8a4606
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Date deposited: 14 Feb 2018 17:30
Last modified: 05 Jun 2024 17:34
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Contributors
Author:
Zoltán Beck
Author:
W. T.Luke Teacy
Author:
Alex Rogers
Author:
Nicholas R. Jennings
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